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You have two simulation types to choose between:  Simulation and  Risk Analysis. Simulation is the traditional way of running your simulation, one run at a time. Risk Analysis, on the other hand, allows you to include uncertainty in your simulation by assigning probability distributions to the assumptions you have made for your model. Studio will use advanced sampling methods to analyze how sensitive your model is to changes in these assumptions.
The  Optimize tool uses advanced goal-seeking methods to find the best set of decisions that fulfill the goals you have set. The tool can be used in both of the simulation types above, allowing you to optimize your model both with and without risk.
You can create  Analysis Variables on any simulation. For ordinary simulations, you can define assumptions, decisions and objectives, while effects are available for risk analyses. In a risk analysis, assumptions can be defined as probability distributions, allowing you to introduce uncertainty into your simulation. Analysis variables may be cloned, allowing you to create sequences of analysis variables with different apply times, for the same model variable.
By combining these various tools and features, you can run a number of useful analyses on your simulation. The various analyses are described in the next sections.
Scenario control and optimisation
 Scenario control
By using decision and assumption analysis variables with ordinary simulation runs, you can program scenarios for your simulation runs. Decisions may also be used to control when the simulation user is allowed to provide input for the simulation, and they also allow you to make decisions for the entire simulation run in advance.
This automated simulation control is available by adding Analysis Variables to a Simulation, and then clicking  Play.
 Optimisation
Powersim Studio automates the search for optimal decisions, saving you a lot of time and increasing the chances of finding the optimal solution. You are even allowed to specify mulitple objectives, and assign importance to each of them. This way you can make tradeoffs between conflicting goals.
Studio automatically serarches for decisions that produce the best results possible. It finds optimal values for decisions and computes a measure for the distance between simulated results and specified objectives. To optimize a policy, Studio needs to know which policy input values and decisions it can vary in order to reach one or more objectives that you have specified. In addition you can specify assumptions about other factors that influence the performance of your system.
Optimisation is available by adding Analysis Variables to a Simulation, and then invoking the Optimize tool.
Risk assessment and risk management
 Risk Assessment
Factors that are external to your organization, such as the inflation rate or other values that are difficult to determine or control, represent risk factors if they seriously affect the results. These are are called assumptions in the model.
Through the risk assessment analysis you can investigate what effects uncertainties in assumptions have on the results. This task finds the probability distributions for the simulated results, based on the specified uncertainties of the assumptions.
You can also use this analysis to find variables that are leverage points for improving performance.
Risk Assessment is available by adding Analysis Variables to a Risk Analysis, and then clicking Play.
 Risk Management
If you have established that your model is sensitive to changes in certain risk factors, you should take them into account when optimizing your policy. Otherwise, the chances of achieving your objectives with a particular policy may be rather low. Through the Risk Management analysis you can find decisions that make your model produce good and robust results. It assures that objectives will be with with a certain level of confidence.
Risk Management is available by adding Analysis Variables to a Risk Analysis, and then invoking the Optimize tool.
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